Close Menu
techwavedispatch.com

    Subscribe to Updates

    Get the latest creative news from FooBar about art, design and business.

    What's Hot

    Hugging Face on AMD Instinct MI300 GPU

    November 12, 2026

    Highly-Accurate Low-Precision Scalar Quantization for LLMs via Gumbel-Softmax Sampling

    November 12, 2026

    Who could replace Jensen Huang? A highly unscientific list of possible successors

    November 12, 2026
    Facebook X (Twitter) Instagram
    Trending
    • Hugging Face on AMD Instinct MI300 GPU
    • Highly-Accurate Low-Precision Scalar Quantization for LLMs via Gumbel-Softmax Sampling
    • Who could replace Jensen Huang? A highly unscientific list of possible successors
    • Deploy models on AWS Inferentia2 from Hugging Face
    • A Comparative Study on IGRA Radiosonde Data
    • An 11B parameter pretrained language model and VLM, trained on over 5000B tokens and 11 languages
    • [2602.12253] Is Online Linear Optimization Sufficient for Strategic Robustness?
    • CyberSecEval 2 – A Comprehensive Evaluation Framework for Cybersecurity Risks and Capabilities of Large Language Models
    Facebook X (Twitter) Instagram
    techwavedispatch.com
    Subscribe
    Thursday, November 12
    • Home
    • AI Tools & Software
    • Machine Learning
    • Generative AI
    • Robotics & Automation
    • Future Tech & Hardware
    • AI in Business
    • Ethics & Regulations
    • More
      • Gadgets & Smart Devices
      • Cybersecurity & AI
      • Tech Breakthroughs
    techwavedispatch.com
    Home»Robotics & Automation»Steering around blockchain hype – O’Reilly
    Robotics & Automation

    Steering around blockchain hype – O’Reilly

    adminBy adminNovember 6, 2026No Comments6 Mins Read
    Facebook Twitter Pinterest LinkedIn Tumblr Email
    Steering around blockchain hype – O’Reilly
    Share
    Facebook Twitter LinkedIn Pinterest Email

    Read “What are Enterprise Blockchains?” and learn how organizations are applying blockchain technology.

    One of the puzzles of the blockchain world is the gap between the enterprise cheerleaders, who want to see a blockchain in anything, and people from the bitcoin world, who frequently don’t see applications of blockchains outside of currency. It’s hardly surprising that there’s a feeding frenzy around any new and cool technology. And it’s to be expected that those who already understand the new technology are more cautious about how it’s applied. But for blockchains, that caution is extreme. Jimmy Song’s recent articles, “Alternatives to Blockchain” and “Why Blockchain Is Hard,” are good examples.

    I know Song, who’s writing a book on bitcoin programming for O’Reilly, and I agree on many of his specific points. Even where I disagree, Song knows a lot more about blockchains than I do. And blockchain advocates need to learn a lot from people who have actually made a blockchain work: there’s a lot of fantasy and unreality at large. Song’s articles should be required reading for anyone considering a blockchain deployment.

    What surprises me is the “it’s our toy and you can’t play with it” attitude that I see coming from much of the bitcoin world. To the extent that there are loads of businesses getting all excited about blockchains when they should just be installing a traditional database, they’re completely right. But to the extent that there are applications for blockchains that we’re only starting to invent, they’re wrong.

    The two blockchain applications that look most interesting to me are Maersk’s container shipping application, and Walmart’s Food Safety Alliance. I’ve actually pooh-poohed the use of blockchains for tracking groceries: tracking every leaf of artisanally grown lettuce as it makes its way to your farmers’ market is the ultimate first-world problem. But when I read about Walmart, I realized that they have a genuine problem managing their supply chains, and it’s a blockchain problem. They’re doing deals with farms all over the world, they have limited ways of tracking what the farms are actually doing or shipping, they don’t know where those products are in the supply chain, and these issues add up to big problems—not just keeping the shelves stocked, but serious health and safety problems.

    It’s probably not a coincidence that the Maersk and Walmart projects are being done in collaboration with IBM and Hyperledger. IBM knows a bit about building large IT projects. Hyperledger Fabric isn’t based on proof-of-work; it is permissioned, significantly increasing transaction throughput and reducing the computational resources required. Many bitcoin purists don’t consider a “permissioned” blockchain a legitimate blockchain. That’s fine with me. I don’t care a whole lot about splitting these semantic hairs. Whatever role enterprise blockchains play in the future, I don’t think they will be based on anything as energy intensive as proof-of-work.

    I am wary of blockchains that don’t cross organizational boundaries. It seems to me that the most important feature of a blockchain is the ability to do trusted computing with untrusted participants. So the first question I’d ask of any blockchain developer is “who don’t you trust?” If the answer is “we trust everyone who is allowed to use our application,” then it’s time to head back to MySQL. In the Maersk and Walmart applications, it’s pretty clear who isn’t trusted. There are plenty of incentives for shippers to forge or falsify paperwork. There are plenty of produce suppliers who might be willing to way “trust me, this lettuce really isn’t from Arizona.”

    I am also wary of re-centralizing something that wants to be decentralized. But I think we have to reconsider what “centralized” means. Let’s imagine an HR blockchain for a large corporation, with tens of thousands of employees. I’m tempted to say that this fails a few of my tests: it’s centralized (probably owned by whoever runs global HR), and there isn’t “distrust”: we have a happy company, working toward common goals, and one big HR group that keeps the paychecks coming. Just use a traditional database and get over your blockchain fascination.

    But that’s not true. I’ve never worked for a large corporation, but even small companies are rarely happy families. They are collections of fiefdoms, many of which don’t trust each other, some of which would gladly stab another group in the back. So maybe an HR blockchain that runs entirely within one company isn’t out of place. It would be an immutable distributed database for performance evaluations, hiring decisions, and other administrative records. A blockchain might make it impossible for HR to say that a harassment complaint against a powerful senior manager was never filed. Maybe such a blockchain would make it possible to distribute control to local working groups, blunting some of the inter-group rivalry. Maybe smart contracts could be developed to manage compliance without requiring a central authority. And in a setting like this, maybe many of the issues that make blockchains hard fall away: you can do updates, you can tolerate relatively slow writes (on some applications), you don’t need a huge number of nodes, and so on. Incentives are less of a problem when they’re derived from real-world situations, like knowing that your employees will be paid fairly, or that Walmart will accept your next shipment of tomatoes.

    It’s certainly possible that enthusiasm for blockchains has prevented developers from investigating simpler, but less trendy, solutions. In an email exchange, Jimmy Song suggests that all three of the applications I’ve mentioned (Maersk, Walmart, and the hypothetical HR application) could be solved more simply with a triple cryptographic signature (two participants plus an auditor). He may be right. But I’m still puzzled: Why not a blockchain? A blockchain is a ledger, but a ledger does more than simply record transactions. A ledger tracks resource flows—for traditional accounting, that resource is cash, but other resources can be tracked, too. And flows are exactly what you care about if you’re dealing with produce supply chains or shipping containers. Until we try both solutions, we won’t know which will work better.

    Most criticisms of enterprise blockchains are making important points. Developers need to understand those criticisms and think seriously about how they apply to their projects. You have to think about the rate at which transactions can be processed, and you have to think about the computing power required. You can’t wish these problems away, or assume that someone else will solve them for you. It’s also important to think about other solutions, and not to be blinded by the blockchain hype.

    But it’s also important not to let criticism limit our imagination. When we finally find the best use cases for blockchains, they may look strange and different, like nothing we would have expected. To discover those applications, we may have to stumble through many poorly thought out experiments and discard lots of poor ideas.

    That’s how technology makes progress.

    Related:

    Learning Path: Introduction to Blockchain Applications — Dr. Jonathan Reichental helps you fully understand the scope of blockchain technology and how it can be used across a variety of applications and industries.

    blockchain hype OReilly Steering
    Share. Facebook Twitter Pinterest LinkedIn Tumblr Email
    admin
    • Website

    Related Posts

    How I detect fake news – O’Reilly

    November 7, 2026

    Robot Videos: Unitree Humanoid, Bio-Inspired Bots, More

    November 7, 2026

    Defensive computing – O’Reilly

    November 7, 2026
    Leave A Reply Cancel Reply

    Top Posts

    NVIDIA Is Investigating Reports That CEO Jensen Huang Was The Target Of Chinese Spy Efforts

    November 8, 202619 Views

    Efficient Vision-Language-Action Model trained on Lerobot Community Data

    November 10, 20264 Views

    Selected-Risk Calibration for Feasibility at Returned Decisions

    November 10, 20263 Views

    Meta releases Muse Ember, a new lightweight model for agent execution

    November 9, 20263 Views
    Don't Miss
    AI Tools & Software

    Hugging Face on AMD Instinct MI300 GPU

    By adminNovember 12, 20260

    Join the next Hugging Cast on June 6th to ask questions to the post authors,…

    Highly-Accurate Low-Precision Scalar Quantization for LLMs via Gumbel-Softmax Sampling

    November 12, 2026

    Who could replace Jensen Huang? A highly unscientific list of possible successors

    November 12, 2026

    Deploy models on AWS Inferentia2 from Hugging Face

    November 12, 2026
    About Us

    Welcome to TechWave Dispatch

    At TechWave Dispatch, we bring you the latest news, insights, and developments from the ever-evolving world of technology. Our mission is to keep readers informed about the innovations shaping our digital future.

    From artificial intelligence and machine learning to cybersecurity, robotics, smart devices, and groundbreaking technologies, we cover the topics that matter in today's fast-moving tech landscape.

    Our Picks

    Hugging Face on AMD Instinct MI300 GPU

    November 12, 2026

    Highly-Accurate Low-Precision Scalar Quantization for LLMs via Gumbel-Softmax Sampling

    November 12, 2026

    Who could replace Jensen Huang? A highly unscientific list of possible successors

    November 12, 2026
    Most Popular

    AI Companies Really, Really Want to Buy Your Work Files and Emails

    November 6, 20260 Views

    Who Controls Scientific Discovery? – O’Reilly

    November 6, 20260 Views

    After blocking Muse, Amazon now lets users text Alexa to help them shop

    November 6, 20260 Views
    Facebook X (Twitter) Instagram Pinterest
    • Terms and Conditions
    • Privacy Policy
    • Contact Us
    • About Us
    © 2026 TechWave Dispatch. All Rights Reserved.

    Type above and press Enter to search. Press Esc to cancel.